Triple
T14600593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Outbreak |
E342692
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object |
Casey Schuler
Casey Schuler is a fictional epidemiologist and disease specialist featured in the medical disaster film "Outbreak."
|
E1120075
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Casey Schuler | Statement: [Outbreak, hasCharacter, Casey Schuler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Casey Schuler Context triple: [Outbreak, hasCharacter, Casey Schuler]
-
A.
Casey Deitz
Casey Deitz is a musician best known as a member of the indie rock band Rogue Wave.
-
B.
Casey Jacobsen
Casey Jacobsen is a former American professional basketball player and sharpshooting guard best known for his standout collegiate career at Stanford and subsequent years in the NBA and top European leagues.
-
C.
Casey Kellog
Casey Kellog is a character from the work "Poor Ophelia," likely serving as a notable figure within its narrative.
-
D.
Casey Klein
Casey Klein is a struggling actress and comedian who works as a cater-waiter in the satirical television series "Party Down."
-
E.
Casey Bourdelle
Casey Bourdelle is a fictional young boy who forms a deep bond with a promising racehorse in the 1978 horse-racing drama film "Casey’s Shadow."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Casey Schuler Triple: [Outbreak, hasCharacter, Casey Schuler]
Generated description
Casey Schuler is a fictional epidemiologist and disease specialist featured in the medical disaster film "Outbreak."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Casey Schuler Target entity description: Casey Schuler is a fictional epidemiologist and disease specialist featured in the medical disaster film "Outbreak."
-
A.
Casey Deitz
Casey Deitz is a musician best known as a member of the indie rock band Rogue Wave.
-
B.
Casey Jacobsen
Casey Jacobsen is a former American professional basketball player and sharpshooting guard best known for his standout collegiate career at Stanford and subsequent years in the NBA and top European leagues.
-
C.
Casey Kellog
Casey Kellog is a character from the work "Poor Ophelia," likely serving as a notable figure within its narrative.
-
D.
Casey Klein
Casey Klein is a struggling actress and comedian who works as a cater-waiter in the satirical television series "Party Down."
-
E.
Casey Bourdelle
Casey Bourdelle is a fictional young boy who forms a deep bond with a promising racehorse in the 1978 horse-racing drama film "Casey’s Shadow."
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d822dec68081908c2553145c4051dc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb438748081908020ce04b869866a |
completed | April 14, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe24a4ceb081908535585175832534 |
completed | May 8, 2026, 6 p.m. |
| NEDg | Description generation | batch_69fe292a5f788190b9871273ac86c2c0 |
completed | May 8, 2026, 6:19 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe2985fc948190864622c1afe9f87a |
completed | May 8, 2026, 6:20 p.m. |
Created at: April 10, 2026, 1:25 a.m.